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Enhanced Conflict Avoidance and Dynamic Path Replanning for Multi-UAVs through MILP with Real-Time Speed and Heading Angle Control

Xiaoqin Liu Bin He ( )Gang Xiao 
Department of Control Science and Engineering, Tongji University, Shanghai 200092, P. R. China
Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 201210, P. R. China
National Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University, Shanghai 201210, P. R. China
Frontiers Science Center for Intelligent Autonomous Systems, Ministry of Education, Shanghai 201210, P. R. China
Shanghai key Laboratory of Intelligent Autonomous Systems, Tongji University, Shanghai 200092, P. R. China
School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, P. R. China

This paper was recommended for publication in its revised form by editorial board member, Jinqiang Cui.

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Abstract

Multi-UAVs operations encounter significant challenges in conflict avoidance and dynamic path replanning, which are crucial for ensuring safety and mission efficiency. To address these challenges, we propose a novel approach using Mixed Integer Linear Programming (MILP) to optimize UAV flight paths through real-time control of speed and heading angles. Our method formulates conflict resolution as an optimal control problem, aiming to minimize adjustments while satisfying constraints such as minimum separation distances, speed limits, and heading angle limits. The MILP algorithm significantly enhances operational efficiency by reducing conflict-related delays and improving mission completion rates. The effectiveness and practicality of the proposed method are validated by integrating speed and heading angle controls, demonstrating enhanced operational efficiency and cost-effectiveness in complex UAV environments.

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Unmanned Systems
Pages 1041-1051

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Cite this article:
Liu X, He B, Xiao G. Enhanced Conflict Avoidance and Dynamic Path Replanning for Multi-UAVs through MILP with Real-Time Speed and Heading Angle Control. Unmanned Systems, 2025, 13(4): 1041-1051. https://doi.org/10.1142/S2301385025500645

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Received: 07 July 2024
Revised: 26 July 2024
Accepted: 03 August 2024
Published: 10 September 2024
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